Biomonitoring of pesticides by pine needles - Chemical scoring, risk of exposure, levels and trends

• Type: Article in International Scientific Journal
• Date: 2014

Authors

Nuno Ratola (Author) FEUP; Vera Homem (Author) FEUP; José Silva (Author) FEUP; Rita Araújo (Author) FEUP; José Manuel Amigo (Author) Other; Lúcia Santos (Author) FEUP; Arminda Alves (Author) FEUP

Journal

Title: Science of the Total Environment

Vol. 476-477

Pages: 114-124

ISSN: 0048-9697

Publisher: Elsevier

Indexing

ISI Web of Knowledge - 19 Citations

ISI Web of Science

Scopus - 24 Citations

Scientific classification

FOS: Engineering and technology > Environmental engineering

CORDIS: Natural sciences > Agrarian Sciences > Soil science > Soil contamination ; Natural sciences > Environmental science > Ecology > Environmental risks ; Natural sciences > Environmental science > Natural resources management > Environmental protection

Associated Projects

SAFEPINE - SAFEPINE - Avaliação da contaminação de pinheiros por poluentes emergentes

Other information

Authenticus ID: P-009-37V

DOI: 10.1016/j.scitotenv.2014.01.003

Abstract (EN): Vegetation is a useful matrix for the quantification of atmospheric pollutants such as semi-volatile organic compounds (SVOCs). In particular, pine needles stand out as effective biomonitors due to the excellent uptake properties of their waxy layer. Having previously validated an original and reliable method to analyse pesticides in pine needles, our work team set the objective of this study to determine the levels of 18 pesticides in Pinus pinea needles collected in 12 different sampling sites in Portugal. These compounds were selected among a total of 70 pesticides by previous chemical scoring, developed to assess their probability to occur in the atmosphere. The risk of exposure was evaluated by the binomial chemical score/frequency of occurrence in the analysed samples. Levels and trends of the chemical families and target of the pesticides were obtained regarding the type of land occupation of the selected sites, including the use of advanced statistics (principal component analysis, PCA). Finally, some correlations with several characteristics of the sampling sites (population, energy consumption, meteorology, etc.) were also investigated.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 11